Preliminary phytochemical studies for the quantification of secondary metabolites of medicinal importance in the plant, Acalypha fruticosa Forssk

The medicinal plant, Acalypha fruticosa Forssk for the treatment of dyspepsia, stomachache, fever, jaundice, skin diseases and even as an antidote is generally distributed in different environments of tropical region in Coimbatore district of Tamil Nadu. However, its occurrence is more common in lower hills of Western Ghats and other habitats in this region where the soil is stony with low moisture. So far, there was no study on the influence of habitat conditions on the change in the content of secondary metabolites of medicinal importance in this plant. Hence to know the changes in the content of such secondary metabolites in the leaves of A. fruticosa, the present study was undertaken in three different habitats. Thin layer chromatography revealed the presence of phytochemical compounds viz., alkaloids, flavonoids and saponins in the leaves of all the three populations. Further the content of all these compounds are found to be higher in the population of dry habitats

Multilayer vectorization to develop a deeper image feature learning model

Computer-Aided Diagnosis (CAD) approaches categorise medical images substantially. Shape, colour, and texture can be problem-specific in medical imagery. Conventional approaches rely largely on them and their relationship, resulting in systems that can\u27t illustrate high-issue domain ideas and have weak prototype generalization. Deep learning techniques deliver an end-to-end model that classifies medical photos thoroughly. Due to the improved medical picture quality and short dataset size, this approach may have high processing costs and model layer restrictions. Multilayer vectorization and the Coding Network-Multilayer Perceptron (CNMP) are merged with deep learning to handle these challenges. This study extracts a high-level characteristic using vectorization, CNN, and conventional characteristics. The model\u27s steps are below. The input picture is vectorized into a few pixels during preprocessing. These pixel images are delivered to a coding network being trained to create high-level classification feature vectors. Medical imaging fundamentals determine picture properties. Finally, neural networks combine the collected features. The recommended technique is tested on ISIC2017 and HIS2828. The model\u27s accuracy is 91% and 92%

Simultano UV-spektrofotometrijsko određivanje ramiprila, acetilsalicilne kiseline i atorvastatin kalcija u kapsulama primjenom kemometrijskih metoda

In the present work, three different spectrophotometric methods for simultaneous estimation of ramipril, aspirin and atorvastatin calcium in raw materials and in formulations are described. Overlapped data was quantitatively resolved by using chemometric methods, viz. inverse least squares (ILS), principal component regression (PCR) and partial least squares (PLS). Calibrations were constructed using the absorption data matrix corresponding to the concentration data matrix. The linearity range was found to be 1-5, 10-50 and 2-10 µg mL–1 for ramipril, aspirin and atorvastatin calcium, respectively. The absorbance matrix was obtained by measuring the zero-order absorbance in the wavelength range between 210 and 320 nm. A training set design of the concentration data corresponding to the ramipril, aspirin and atorvastatin calcium mixtures was organized statistically to maximize the information content from the spectra and to minimize the error of multivariate calibrations. By applying the respective algorithms for PLS 1, PCR and ILS to the measured spectra of the calibration set, a suitable model was obtained. This model was selected on the basis of RMSECV and RMSEP values. The same was applied to the prediction set and capsule formulation. Mean recoveries of the commercial formulation set together with other figures of merit (calibration sensitivity, selectivity, limit of detection, limit of quantification and analytical sensitivity) were estimated. Validity of the proposed approaches was successfully assessed for analyses of drugs in the various prepared physical mixtures and formulations.U radu su opisane tri različite spektrofotometrijske metode za određivanje ramiprila, acetilsalicilne kiseline i atorvastatin kalcija u sirovinama i formulacijama. Preklapanje podataka kvantitativno je riješeno pomoću kemometrijskih metoda, tj. metodama inverznih najmanjih kvadrata (ILS), regresije glavnog sastojka (PCR) i djelomičnih najmanjih kvadrata (PLS). Kalibracije su postavljene pomoću matrice podataka za apsorpciju koja odgovara matrici pripadajućih koncentracija. Područje linearnosti za ramipril iznosilo je 1–5, za acetilsalicilnu kiselinu 10–50, a za atorvastatin kalcij 2–10 µg mL–1. Matrica s apsorbancijama dobivena je mjerenjem apsorbancije nultog reda na valnim duljinama između 210 i 320 nm. Set podataka za koncentracije ramiprila, acetilsalicilne kiseline i atorvastatin kalcija u smjesi statistički je tako organiziran da osigura maksimalnu količinu informacije u spektrima i minimalizira grešku multivarijantnih kalibracija. Primjenom odgovarajućih algoritama za PLS, PCR i ILS na snimljene spektre kalibracijskog seta dobiven je dobar model, koji je odabran na temelju RMSECV i RMSEP vrijednosti. Isti model je primijenjen i na set s predviđenim vrijednostima i na kapsule sa smjesom ove tri ljekovite tvari. Određena je srednja vrijednost povrata za komercijalnu formulaciju te ostale analitičke izvedbene značajke (kalibracijska osjetljivost, selektivnost, granica dokazivanja, granica određivanja i analitička osjetljivost). Potvrđena je primjenjljivost predloženih metoda u analizama lijekova u fizičkim smjesama i u gotovim ljekovitim oblicima

Metformin modulates microbiota and improves blood pressure and cardiac remodeling in a rat model of hypertension

Aims Metformin has been attributed to cardiovascular protection even in the absence of diabetes. Recent observations suggest that metformin influences the gut microbiome. We aimed to investigate the influence of metformin on the gut microbiota and hypertensive target organ damage in hypertensive rats. Methods Male double transgenic rats overexpressing the human renin and angiotensinogen genes (dTGR), a model of angiotensin II‐dependent hypertension, were treated with metformin (300 mg/kg/day) or vehicle from 4 to 7 weeks of age. We assessed gut microbiome composition and function using shotgun metagenomic sequencing and measured blood pressure via radiotelemetry. Cardiac and renal organ damage and inflammation were evaluated by echocardiography, histology, and flow cytometry. Results Metformin treatment increased the production of short‐chain fatty acids (SCFA) acetate and propionate in feces without altering microbial composition and diversity. It significantly reduced systolic and diastolic blood pressure and improved cardiac function, as measured by end‐diastolic volume, E/A, and stroke volume despite increased cardiac hypertrophy. Metformin reduced cardiac inflammation by lowering macrophage infiltration and shifting macrophage subpopulations towards a less inflammatory phenotype. The observed improvements in blood pressure, cardiac function, and inflammation correlated with fecal SCFA levels in dTGR. In vitro, acetate and propionate altered M1‐like gene expression in macrophages, reinforcing anti‐inflammatory effects. Metformin did not affect hypertensive renal damage or microvascular structure. Conclusion Metformin modulated the gut microbiome, increased SCFA production, and ameliorated blood pressure and cardiac remodeling in dTGR. Our findings confirm the protective effects of metformin in the absence of diabetes, highlighting SCFA as a potential mediators

Phage Displayed Short Peptides against Cells of Candida albicans Demonstrate Presence of Species, Morphology and Region Specific Carbohydrate Epitopes

Candida albicans is a commensal opportunistic pathogen, which can cause superficial infections as well as systemic infections in immuocompromised hosts. Among nosocomial fungal infections, infections by C. albicans are associated with highest mortality rates even though incidence of infections by other related species is on the rise world over. Since C. albicans and other Candida species differ in their susceptibility to antifungal drug treatment, it is crucial to accurately identify the species for effective drug treatment. Most diagnostic tests that differentiate between C. albicans and other Candida species are time consuming, as they necessarily involve laboratory culturing. Others, which employ highly sensitive PCR based technologies often, yield false positives which is equally dangerous since that leads to unnecessary antifungal treatment. This is the first report of phage display technology based identification of short peptide sequences that can distinguish C. albicans from other closely related species. The peptides also show high degree of specificity towards its different morphological forms. Using fluorescence microscopy, we show that the peptides bind on the surface of these cells and obtained clones that could even specifically bind to only specific regions of cells indicating restricted distribution of the epitopes. What was peculiar and interesting was that the epitopes were carbohydrate in nature. This gives insight into the complexity of the carbohydrate composition of fungal cell walls. In an ELISA format these peptides allow specific detection of relatively small numbers of C. albicans cells. Hence, if used in combination, such a test could help accurate diagnosis and allow physicians to initiate appropriate drug therapy on time

Circulating extracellular vesicles as putative mediators of cardiovascular disease in paediatric chronic kidney disease

Cardiovascular disease (CVD) is the leading cause of mortality in chronic kidney disease (CKD). However, the pathogenesis of CVD in CKD remains incompletely understood. Endothelial extracellular vesicles (EC-EVs) have previously been associated with CVD. We hypothesized that CKD alters EV release and cargo, subsequently promoting vascular remodelling. We recruited 94 children with CKD, including patients after kidney transplantation and healthy donors, and performed EV phenotyping and functional EV analyses in the absence of age-related comorbidities. Plasma EC-EVs were increased in haemodialysis patients and decreased after kidney transplantation. Thirty microRNAs were less abundant in total CKD plasma EVs with predicted importance in angiogenesis and smooth muscle cell proliferation. In vitro, CKD plasma EVs induced transcriptomic changes in angiogenesis pathways and functionally impaired angiogenic properties, migration and proliferation in ECs. High shear stress, as generated by arterio-venous fistulas, and uremic toxins were considered as potential drivers of EV release, but only the combination increased EV generation from venous ECs. The resulting EVs recapitulated miRNA changes observed in CKD in vivo. In conclusion, CKD results in the release of EVs with altered miRNA profiles and anti-angiogenic properties, which may mediate vascular pathology in children with CKD. EVs and their miRNA cargo may represent future therapeutic targets to attenuate CVD in CKD

Simultaneous Estimation of Paracetamol, Ambroxol Hydrochloride, Levocetirizine Dihydrochloride, and Phenylephrine Hydrochloride in Combined Tablet Formulation by First-Order Derivative Spectrophotometry

Paracetamol, ambroxol hydrochloride, levocetirizine dihydrochloride, and phenylephrine hydrochloride are used in combination for the treatment of chronic sinusitis, rhinitis, fever, nasal discharge, sore throat, and wheezing. The present work deals with method development for simultaneous estimation of paracetamol, ambroxol hydrochloride, levocetirizine dihydrochloride, and phenylephrine hydrochloride in tablet formulation by first-order derivative spectrosphotometry. For determination of sampling wavelength, 10 μg/mL of each of paracetamol, ambroxol hydrochloride, levocetirizine dihydrochloride, and phenylephrine hydrochloride was scanned in 200–400 nm ranges and sampling wavelengths were found to be 305.5 nm for paracetamol, 321 nm for ambroxol hydrochloride, 244 nm for levocetirizine dihydrochloride, and 280 nm for phenylephrine hydrochloride in first-order derivative spectrophotometry. In this method, linearity was observed in the ranges of 20–140 μg/mL for paracetamol and 10–70 μg/mL for ambroxol hydrochloride, levocetirizine dihydrochloride, and phenylephrine hydrochloride. The % recovery was within the range between 98 and 102%, and % relative standard deviation for precision and accuracy of the method was found to be less than 2%. The method is validated as per International Conference on Harmonization Guidelines. The method can be successfully applied for the simultaneous analysis of these drugs in pharmaceutical dosage forms.</jats:p